Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations2969
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory278.3 KiB
Average record size in memory96.0 B

Variable types

Numeric11

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticketHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 2 other fieldsHigh correlation
invoice_no is highly overall correlated with gross_revenue and 2 other fieldsHigh correlation
quantity is highly overall correlated with avg_basket_size and 2 other fieldsHigh correlation
recency_days is highly overall correlated with invoice_noHigh correlation
avg_ticket is highly skewed (γ1 = 53.44421547)Skewed
qty_returns is highly skewed (γ1 = 52.70290171)Skewed
avg_basket_size is highly skewed (γ1 = 44.67431359)Skewed
customer_id has unique valuesUnique
recency_days has 34 (1.1%) zerosZeros
qty_returns has 1481 (49.9%) zerosZeros

Reproduction

Analysis started2024-08-05 14:31:03.656557
Analysis finished2024-08-05 14:31:12.628896
Duration8.97 seconds
Software versionydata-profiling vv4.9.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct2969
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.773
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:12.680697image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.4
Q113799
median15221
Q316768
95-th percentile17964.6
Maximum18287
Range5940
Interquartile range (IQR)2969

Descriptive statistics

Standard deviation1718.9903
Coefficient of variation (CV)0.11256734
Kurtosis-1.2060947
Mean15270.773
Median Absolute Deviation (MAD)1488
Skewness0.031607859
Sum45338925
Variance2954927.6
MonotonicityNot monotonic
2024-08-05T11:31:12.769641image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12558 1
 
< 0.1%
17850 1
 
< 0.1%
13047 1
 
< 0.1%
12583 1
 
< 0.1%
13748 1
 
< 0.1%
15100 1
 
< 0.1%
15291 1
 
< 0.1%
14688 1
 
< 0.1%
17809 1
 
< 0.1%
16956 1
 
< 0.1%
Other values (2959) 2959
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

HIGH CORRELATION 

Distinct2954
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2747.1004
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:12.853993image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.77
Q1570.96
median1084.1
Q32308.06
95-th percentile7219.68
Maximum279138.02
Range279131.82
Interquartile range (IQR)1737.1

Descriptive statistics

Standard deviation10560.058
Coefficient of variation (CV)3.8440742
Kurtosis355.5067
Mean2747.1004
Median Absolute Deviation (MAD)672.05
Skewness16.802797
Sum8156141.2
Variance1.1151482 × 108
MonotonicityNot monotonic
2024-08-05T11:31:12.940227image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
379.65 2
 
0.1%
731.9 2
 
0.1%
1353.74 2
 
0.1%
889.93 2
 
0.1%
331 2
 
0.1%
745.06 2
 
0.1%
2092.32 2
 
0.1%
2053.02 2
 
0.1%
1025.44 2
 
0.1%
734.94 2
 
0.1%
Other values (2944) 2949
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
136263.72 1
< 0.1%
124564.53 1
< 0.1%
116725.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency_days
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.288649
Minimum0
Maximum373
Zeros34
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:13.025996image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.756171
Coefficient of variation (CV)1.2094852
Kurtosis2.7780386
Mean64.288649
Median Absolute Deviation (MAD)26
Skewness1.7983969
Sum190873
Variance6046.0221
MonotonicityNot monotonic
2024-08-05T11:31:13.117195image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
3 85
 
2.9%
2 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
22 55
 
1.9%
Other values (262) 2219
74.7%
ValueCountFrequency (%)
0 34
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

invoice_no
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7217918
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:13.209921image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.847316
Coefficient of variation (CV)1.5462492
Kurtosis190.04523
Mean5.7217918
Median Absolute Deviation (MAD)2
Skewness10.743151
Sum16988
Variance78.275
MonotonicityNot monotonic
2024-08-05T11:31:13.296724image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 786
26.5%
3 498
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 70
 
2.4%
10 54
 
1.8%
Other values (47) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 786
26.5%
3 498
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 70
 
2.4%
10 54
 
1.8%
ValueCountFrequency (%)
206 1
< 0.1%
198 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

quantity
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.618727
Minimum1
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:13.383472image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q18
median11
Q314
95-th percentile22
Maximum102
Range101
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.2644549
Coefficient of variation (CV)0.53916879
Kurtosis25.417776
Mean11.618727
Median Absolute Deviation (MAD)3
Skewness3.1030188
Sum34496
Variance39.243396
MonotonicityNot monotonic
2024-08-05T11:31:13.475203image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
10 288
 
9.7%
9 260
 
8.8%
11 255
 
8.6%
12 220
 
7.4%
8 219
 
7.4%
7 210
 
7.1%
13 200
 
6.7%
14 165
 
5.6%
6 157
 
5.3%
15 137
 
4.6%
Other values (38) 858
28.9%
ValueCountFrequency (%)
1 19
 
0.6%
2 32
 
1.1%
3 60
 
2.0%
4 82
 
2.8%
5 107
 
3.6%
6 157
5.3%
7 210
7.1%
8 219
7.4%
9 260
8.8%
10 288
9.7%
ValueCountFrequency (%)
102 1
 
< 0.1%
74 1
 
< 0.1%
58 2
0.1%
57 1
 
< 0.1%
56 1
 
< 0.1%
54 1
 
< 0.1%
50 2
0.1%
49 3
0.1%
44 4
0.1%
43 1
 
< 0.1%

avg_ticket
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2966
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.893306
Minimum2.1505882
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:13.770298image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.9166611
Q113.119333
median17.940811
Q324.97963
95-th percentile90.497
Maximum56157.5
Range56155.349
Interquartile range (IQR)11.860296

Descriptive statistics

Standard deviation1036.9345
Coefficient of variation (CV)19.982048
Kurtosis2890.7065
Mean51.893306
Median Absolute Deviation (MAD)5.9641157
Skewness53.444215
Sum154071.22
Variance1075233.2
MonotonicityNot monotonic
2024-08-05T11:31:13.867751image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
0.1%
4.162 2
 
0.1%
14.47833333 2
 
0.1%
3.411945289 1
 
< 0.1%
16.29372093 1
 
< 0.1%
36.24411765 1
 
< 0.1%
29.78416667 1
 
< 0.1%
22.8792623 1
 
< 0.1%
20.51104167 1
 
< 0.1%
149.025 1
 
< 0.1%
Other values (2956) 2956
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%

avg_recency_days
Real number (ℝ)

HIGH CORRELATION 

Distinct290
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.092287
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:13.960830image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q125
median48
Q385
95-th percentile201
Maximum366
Range365
Interquartile range (IQR)60

Descriptive statistics

Standard deviation63.614645
Coefficient of variation (CV)0.94816629
Kurtosis4.8867434
Mean67.092287
Median Absolute Deviation (MAD)26
Skewness2.0639464
Sum199197
Variance4046.823
MonotonicityNot monotonic
2024-08-05T11:31:14.071852image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 49
 
1.7%
14 45
 
1.5%
46 43
 
1.4%
21 43
 
1.4%
22 43
 
1.4%
38 42
 
1.4%
28 41
 
1.4%
26 41
 
1.4%
17 41
 
1.4%
27 41
 
1.4%
Other values (280) 2540
85.6%
ValueCountFrequency (%)
1 17
0.6%
2 15
0.5%
3 19
0.6%
4 27
0.9%
5 18
0.6%
6 21
0.7%
7 31
1.0%
8 24
0.8%
9 27
0.9%
10 27
0.9%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
363 1
 
< 0.1%
362 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

HIGH CORRELATION 

Distinct1349
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.063268815
Minimum0.0054495913
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:14.161318image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0094339623
Q10.017777778
median0.029411765
Q30.055401662
95-th percentile0.22222222
Maximum3
Range2.9945504
Interquartile range (IQR)0.037623884

Descriptive statistics

Standard deviation0.13447745
Coefficient of variation (CV)2.1254933
Kurtosis121.57483
Mean0.063268815
Median Absolute Deviation (MAD)0.014338235
Skewness8.7739699
Sum187.84511
Variance0.018084183
MonotonicityNot monotonic
2024-08-05T11:31:14.256169image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3333333333 21
 
0.7%
0.1666666667 21
 
0.7%
0.02777777778 20
 
0.7%
0.09090909091 19
 
0.6%
0.0625 17
 
0.6%
0.4 16
 
0.5%
0.1333333333 16
 
0.5%
0.02380952381 15
 
0.5%
0.25 15
 
0.5%
0.03571428571 15
 
0.5%
Other values (1339) 2794
94.1%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
2 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.5 3
 
0.1%
1 14
0.5%
0.8333333333 1
 
< 0.1%
0.75 1
 
< 0.1%
0.6666666667 12
0.4%
0.6487935657 1
 
< 0.1%
0.6 1
 
< 0.1%

qty_returns
Real number (ℝ)

SKEWED  ZEROS 

Distinct173
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.255978
Minimum0
Maximum80995
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:14.349067image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile63
Maximum80995
Range80995
Interquartile range (IQR)6

Descriptive statistics

Standard deviation1503.4837
Coefficient of variation (CV)28.771515
Kurtosis2833.6407
Mean52.255978
Median Absolute Deviation (MAD)1
Skewness52.702902
Sum155148
Variance2260463.1
MonotonicityNot monotonic
2024-08-05T11:31:14.445260image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
1 295
 
9.9%
3 169
 
5.7%
6 93
 
3.1%
2 87
 
2.9%
4 71
 
2.4%
5 43
 
1.4%
12 43
 
1.4%
8 40
 
1.3%
7 38
 
1.3%
Other values (163) 609
20.5%
ValueCountFrequency (%)
0 1481
49.9%
1 295
 
9.9%
2 87
 
2.9%
3 169
 
5.7%
4 71
 
2.4%
5 43
 
1.4%
6 93
 
3.1%
7 38
 
1.3%
8 40
 
1.3%
9 36
 
1.2%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
4824 1
< 0.1%
4027 1
< 0.1%
2302 2
0.1%
1776 1
< 0.1%
1608 1
< 0.1%
1589 1
< 0.1%
1515 1
< 0.1%
1278 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

HIGH CORRELATION 

Distinct1009
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.15117
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:14.538963image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3454545
Q110
median17.2
Q327.75
95-th percentile56.94
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.512963
Coefficient of variation (CV)0.88089984
Kurtosis27.697928
Mean22.15117
Median Absolute Deviation (MAD)8.2
Skewness3.4988031
Sum65766.825
Variance380.75571
MonotonicityNot monotonic
2024-08-05T11:31:14.631069image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 54
 
1.8%
14 40
 
1.3%
11 38
 
1.3%
9 33
 
1.1%
18 33
 
1.1%
1 32
 
1.1%
20 31
 
1.0%
10 30
 
1.0%
16 29
 
1.0%
17 28
 
0.9%
Other values (999) 2621
88.3%
ValueCountFrequency (%)
1 32
1.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

avg_basket_size
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1974
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.39271
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2024-08-05T11:31:14.723643image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.25
median172
Q3281.5
95-th percentile599.52
Maximum40498.5
Range40497.5
Interquartile range (IQR)178.25

Descriptive statistics

Standard deviation791.55574
Coefficient of variation (CV)3.173933
Kurtosis2255.6274
Mean249.39271
Median Absolute Deviation (MAD)82.75
Skewness44.674314
Sum740446.95
Variance626560.48
MonotonicityNot monotonic
2024-08-05T11:31:14.826108image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
86 9
 
0.3%
73 9
 
0.3%
82 9
 
0.3%
136 8
 
0.3%
60 8
 
0.3%
163 8
 
0.3%
88 8
 
0.3%
140 8
 
0.3%
Other values (1964) 2881
97.0%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%

Interactions

2024-08-05T11:31:11.665338image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:03.832654image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.622690image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.357183image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.227689image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.919537image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.627015image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.342134image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.123637image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.038001image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.840550image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.739123image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:03.898596image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.683670image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.423138image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.287267image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.988406image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.688776image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.411379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.188426image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.104926image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.908221image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.805935image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:03.990246image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.743327image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.484978image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.346171image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.056655image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.750689image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.475999image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.432740image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.171602image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.972460image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.874218image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.059187image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.821854image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.551224image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.414954image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.121316image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.817035image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.549217image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.500074image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.243356image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.037914image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.939103image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.121206image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.892999image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.612062image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.470968image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.178676image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.875632image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.612030image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.559252image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.313022image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.097526image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:12.003687image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.182111image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.956675image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.675013image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.529122image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.239118image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.938099image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.681214image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.622244image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.379601image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.169258image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:12.071427image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.244830image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.016646image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.738279image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.591396image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.298290image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.006100image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.760593image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.692652image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.447050image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.233459image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:12.143672image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.311113image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.082137image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.955693image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.656212image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.364108image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.077018image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.841434image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.760729image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.526649image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.300233image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:12.212765image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.374000image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.145071image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.021419image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.719533image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.427497image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.141587image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.910256image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.824526image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.624366image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.409714image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:12.290397image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.442409image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.224785image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.091784image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.789623image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.495365image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.210403image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.986701image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.898261image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.697879image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.526869image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:12.359352image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:04.527395image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:05.290693image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.156765image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:06.851180image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:07.559174image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:08.273625image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.053182image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:09.966785image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:10.767244image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-08-05T11:31:11.590744image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Correlations

2024-08-05T11:31:14.901145image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueinvoice_noqty_returnsquantityrecency_days
avg_basket_size1.000-0.0770.1890.448-0.1230.0570.5760.1010.2100.518-0.098
avg_recency_days-0.0771.000-0.1220.0480.019-0.961-0.250-0.262-0.392-0.1810.109
avg_ticket0.189-0.1221.000-0.611-0.1300.0970.2460.0610.198-0.0750.047
avg_unique_basket_size0.4480.048-0.6111.000-0.007-0.0420.2910.0260.0060.446-0.107
customer_id-0.1230.019-0.130-0.0071.000-0.008-0.0760.025-0.064-0.0070.001
frequency0.057-0.9610.097-0.042-0.0081.0000.1600.1480.3530.109-0.031
gross_revenue0.576-0.2500.2460.291-0.0760.1601.0000.7710.3590.770-0.415
invoice_no0.101-0.2620.0610.0260.0250.1480.7711.0000.2830.660-0.502
qty_returns0.210-0.3920.1980.006-0.0640.3530.3590.2831.0000.262-0.115
quantity0.518-0.181-0.0750.446-0.0070.1090.7700.6600.2621.000-0.399
recency_days-0.0980.1090.047-0.1070.001-0.031-0.415-0.502-0.115-0.3991.000

Missing values

2024-08-05T11:31:12.459856image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-08-05T11:31:12.574159image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysinvoice_noquantityavg_ticketavg_recency_daysfrequencyqty_returnsavg_unique_basket_sizeavg_basket_size
017850.05391.21372.034.06.018.15222235.00.48611121.08.73529450.970588
113047.03232.5956.09.011.018.90403527.00.0487806.019.000000154.444444
212583.06705.382.015.024.028.90250023.00.04569950.015.466667335.200000
313748.0948.2595.05.08.033.86607192.00.0179210.05.60000087.800000
415100.0876.00333.03.02.0292.0000008.00.13636422.01.00000026.666667
515291.04623.3025.014.017.045.32647123.00.05444127.07.285714150.142857
614688.05630.877.021.024.017.21978618.00.073569281.015.571429172.428571
717809.05411.9116.012.023.088.71983635.00.03910641.05.083333171.416667
815311.060767.900.091.043.025.5434644.00.315508231.026.142857419.714286
916098.02005.6387.07.015.029.93477647.00.0243900.09.57142987.571429
customer_idgross_revenuerecency_daysinvoice_noquantityavg_ticketavg_recency_daysfrequencyqty_returnsavg_unique_basket_sizeavg_basket_size
562717727.01060.2515.01.011.016.0643946.00.2857146.066.0645.000000
563717232.0421.522.02.010.011.70888912.00.1538460.018.0101.500000
563817468.0137.0010.02.02.027.4000004.00.4000000.02.558.000000
564913596.0697.045.02.010.04.1990367.00.2500000.083.0203.000000
565514893.01237.859.02.014.016.9568492.00.6666670.036.5399.500000
565912479.0473.2011.01.08.015.7733334.00.33333334.030.0382.000000
568014126.0706.137.03.06.047.0753333.01.00000050.05.0169.333333
568613521.01092.391.03.09.02.5112414.00.3000000.0145.0244.333333
569615060.0301.848.04.08.02.5153331.02.0000000.030.065.500000
571512558.0269.967.01.05.024.5418186.00.285714102.011.0196.000000